Finding least-cost paths across a continuous raster surface with discrete vector networks

The problem of finding the least-cost path from a source point to a destination point can be dealt with by routing across a continuous surface or routing along a discrete network. The solutions within these two contexts are linked to the use of a raster- or a vector-based least-cost path algorithm. This study presents a technique which integrates raster- and vector-based least-cost path algorithms for determining the least-cost path across a continuous raster surface with discrete vector networks. The technique incorporates ancillary vector data sets that are required to examine the travel cost at each link, connections between nodes, and the representation of intersecting links in the discrete vector network into raster-based least-cost path analysis. The integrated technique presented here is applicable to all-terrain vehicle navigation where a continuous raster surface and discrete vector networks need to be considered simultaneously in order to find least-cost paths. This paper describes the concept behind, and details of, the integrated technique. Applications of the technique with synthetic and real-world data sets are also presented. They provide proof that the technique is effective in finding least-cost paths across a continuous raster surface with discrete vector networks.

[1]  Keith C. Clarke,et al.  Multi‐criteria evaluation and least‐cost path analysis for optimal haulage routing of dump trucks in large scale open‐pit mines , 2009, Int. J. Geogr. Inf. Sci..

[2]  Peng Gao,et al.  A Directional Path Distance Model for Raster Distance Mapping , 1993, COSIT.

[3]  Jianping Xu,et al.  Improving Simulation Accuracy of Spread Phenomena in a Raster-Based Geographic Information System , 1995, Int. J. Geogr. Inf. Sci..

[4]  Jay Lee,et al.  Research Article: Extensions to least-cost path algorithms for roadway planning , 2003, Int. J. Geogr. Inf. Sci..

[5]  Manoj K. Arora,et al.  GIS‐based route planning in landslide‐prone areas , 2005, Int. J. Geogr. Inf. Sci..

[6]  Q. Wu,et al.  A shortest path algorithm with novel heuristics for dynamic transportation networks , 2007, Int. J. Geogr. Inf. Sci..

[7]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[8]  Dennis R Becker,et al.  Ecological criteria, participant preferences and location models: a GIS approach toward ATV trail planning. , 2008 .

[9]  Jay Lee,et al.  On Applying Viewshed Analysis for Determining Least-Cost Paths on Digital Elevation Models , 1998, Int. J. Geogr. Inf. Sci..

[10]  Yosoon Choi,et al.  Optimal haulage routing of off-road dump trucks in construction and mining sites using Google Earth and a modified least-cost path algorithm , 2011 .

[11]  Alexandre B. Gonçalves,et al.  An extension of GIS-based least-cost path modelling to the location of wide paths , 2010, Int. J. Geogr. Inf. Sci..

[12]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[13]  C. Dana Tomlin,et al.  Propagating radial waves of travel cost in a grid , 2010, Int. J. Geogr. Inf. Sci..

[14]  Walter Collischonn,et al.  A direction dependent least-cost-path algorithm for roads and canals , 2000, Int. J. Geogr. Inf. Sci..